Learning a potential function \(\Phi (s)\)  using Meta-Learning in order to accelerate the learning is studied in [1]}. The potential function is defined as a neural network and its parameters are updated using Model-Agnostic Meta-Learning (MAML) algorithm [2]}. The updating equations of MAML are as follows.
\(\phi _i=\theta -\alpha \nabla _\theta \mathcal {L}_{\tau _i}(f_\theta )\) 
\(\theta =\theta -\beta \nabla _\theta \mathbb {E}_{\tau _{i}}\mathcal {L}_{\tau _i}(f_{\phi _i})\) 
